Jonas Rauber - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 7 from 7

2021

Advances in Reliably Evaluating and Improving Adversarial RobustnessJonas Rauber. PhD thesis, University of Tübingen, Germany, 2021. [doi]

2020

Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established AttacksFrancesco Croce, Jonas Rauber, Matthias Hein 0001. ijcv, 128(4):1028-1046, 2020. [doi]

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAXJonas Rauber, Roland S. Zimmermann, Matthias Bethge, Wieland Brendel. jossw, 5(53):2607, 2020. [doi]

2019

Accurate, reliable and fast robustness evaluationWieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge. nips 2019: 12841-12851 [doi]

Towards the first adversarially robust neural network model on MNISTLukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel. iclr 2019: [doi]

2018

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning ModelsWieland Brendel, Jonas Rauber, Matthias Bethge. iclr 2018: [doi]

Generalisation in humans and deep neural networksRobert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann. nips 2018: 7549-7561 [doi]

Sign in or sign up to see more results.

runs on WebDSL